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At least 667 records · Page 37

Chapter 4: Wind Energy Politics and Economics

A new paradigm for wind energy policy is emerging that is driven by rapidly decreasing costs, increasing market share and the need for more energy system services provided by wind energy. Increased recognition of the diversity of policy needs, tailored to the conditions of each respective jurisdiction, is another significant aspect of this new paradigm. This evolving perspective has come about as onshore wind energy has become the most competitive technology for new energy production in many countries, reducing the need for direct financial support. Accordingly, while the need for wind energy policy support continues, it is becoming increasingly nuanced and focused on serving an array of social objectives associated with the broader evolution of the energy sector. In the future, successful wind energy policies will increasingly be related to creating enabling environments and adapting frameworks, as opposed to focusing on direct investment incentives alone. This reflects a fundamental shift in the perspectives and roles of policy-makers. This is the focus of this chapter, in which we first provide an overview of the state of the art in wind energy policy, followed by upcoming policy challenges and research needs. We conclude with our perspective on the future focus of wind energy policy research.

policy↗

Further Insights on the Influence of the Indian Ocean Dipole on the Following Year’s ENSO from Observations and CMIP5 Models

Recent observational studies have suggested that negative and positive Indian Ocean dipole (IOD) events (nIOD and pIOD, respectively) favor a transition toward, respectively, El Niño and La Niña events one year later. These statistical inferences are however limited by the length and uncertainties in the observational records. This paper compares observational datasets with twenty-one 155-yr historical simulations from phase 5 of CMIP (CMIP5) to assess IOD and El Niño–Southern Oscillation (ENSO) properties along with their synchronous and delayed relationships. In the observations and most CMIP5 models, it is shown that El Niños tend to be followed by La Niñas but not the opposite, that pIODs co-occur more frequently with El Niños than nIODs with La Niñas, that nIODs tend to be followed by El Niños one year later less frequently than pIODs by La Niñas, and that including an IOD index in a linear prediction based on the Pacific warm water volume improves ENSO peak hindcasts at 14 months lead. The IOD–ENSO delayed relationship partly results from a combination of ENSO intrinsic properties (e.g., the tendency for El Niños to be followed by La Niñas) and from the synchronous IOD–ENSO relationship. The results, however, reveal that this is not sufficient to explain the high prevalence of pIOD–Niña transitions in the observations and 75% of the CMIP5 models, and of nIOD–Niño transitions in 60% of CMIP5 models. Lastly, this suggests that the tendency of IOD to lead ENSO by one year should be explained by a physical mechanism that, however, remains elusive in the CMIP5 models. The ability of many CMIP5 models to reproduce the delayed influence of the IOD on ENSO is nonetheless a strong incentive to explore extended-range dynamical forecasts of ENSO.

54 ENVIRONMENTAL SCIENCES↗

Extreme heat vulnerability of manufactured housing in arid urban environments

This article explores the role of land cover in relation to housing type and tenure in shaping exposure to extreme urban heat, focusing on residents of mobile and manufactured housing (MH). We hypothesize that MH residents will experience greater exposure to extreme heat than those living in other housing types due to lower levels of proximate vegetation. This hypothesis is based on the unique property relations and tenure regimes that characterize MH, which may disincentivize investments in planting and maintaining trees and vegetation in arid environments. To test this hypothesis, we compare the amount of vegetation on properties across housing types, within-type tenure arrangements and between three urbanized areas in Arizona with different levels of exposure to extreme heat. To conduct this comparison, we combine multispectral land cover data for 1.7 million parcels with tax assessor data and building footprints to measure land cover at a high resolution. We find that MH units have significantly less vegetation than single-family residential properties, and that MH units in MH parks have less vegetation than those on individual lots. We conclude that municipalities should promote (e.g. through incentives or other policy interventions) the planting of more vegetation around MH units where there is a risk of extreme heat exposure. Future research can expand this analysis with a closer examination of how municipal ordinances and policies affect land cover by housing type and tenure.

heat↗

Opportunities for and challenges to further reductions in the “specific power” rating of wind turbines installed in the United States

A wind turbine’s “specific power” rating relates its capacity to the swept area of its rotor in terms of Watt per square meter. For a given generator capacity, specific power declines as rotor size increases. In land-rich but capacity-constrained wind power markets, such as the United States, developers have an economic incentive to maximize megawatt-hours per constrained megawatt, and so have favored turbines with ever-lower specific power. To date, this trend toward lower specific power has pushed capacity factors higher while reducing the levelized cost of energy. We employ geospatial levelized cost of energy analysis across the United States to explore whether this trend is likely to continue. We find that under reasonable cost scenarios (i.e. presuming that logistical challenges from very large blades are surmountable), low-specific-power turbines could continue to be in demand going forward. Beyond levelized cost of energy, the boost in market value that low-specific-power turbines provide could become increasingly important as wind penetration grows.

geospatial modeling↗

Interactions Between Climate Policy and Technology-influenced Travel Behavior: Mitigating Induced Demand from CACC

Advances in vehicle technology have influenced the development of automated vehicle systems, where vehicles that do not require human intervention are already deployed in the roadway networks. While these advances are proved to increase roadway safety and highway capacity, more research is needed to understand the long-term and regional-level impacts on mobility, land use, energy consumption, and emissions. This study proposes a multi-model approach to analyze the effect of vehicle automation and deep decarbonization policies over a period from 2020 to 2040 in Austin, Texas. We use the Global Change Analysis Model (GCAM) to develop internally the scenarios that are then passed to the SMART Mobility modeling workflow, a large-scale simulation framework combining the POLARIS activity-based travel demand model and mesoscopic traffic simulator with the Autonomie vehicle energy consumption model and the UrbanSim land use simulator. Results suggest that the introduction of vehicles with advanced automation could increase fuel consumption when no decarbonization policies are implemented. Also, advances in vehicle technology research and development could lead to a decline in energy use in the long-term. Energy pricing and vehicle electrification incentives could help reduce the impact of vehicle automation. Finally, our analysis indicates the relevance of introducing land use processes in longterm vehicle automation studies.

land use↗

Potential long-term, global effects of enhancing the domestic terrestrial carbon sink in the United States through no-till and cover cropping

Abstract Background Achieving a net zero greenhouse gas United States (US) economy is likely to require both deep sectoral mitigation and additional carbon dioxide removals to offset hard-to-abate emissions. Enhancing the terrestrial carbon sink, through practices such as the adoption of no-till and cover cropping agricultural management, could provide a portion of these required offsets. Changing domestic agricultural practices to optimize carbon content, however, might reduce or shift US agricultural commodity outputs and exports, with potential implications on respective global markets and land use patterns. Here, we use an integrated energy-economy-land-climate model to comprehensively assess the global land, trade, and emissions impacts of an adoption of domestic no-till farming and cover cropping practices based on carbon pricing. Results We find that the adoption of these practices varies depending on which aspects of terrestrial carbon are valued. Valuation of all terrestrial carbon resulted in afforestation at the expense of domestic agricultural production. In contrast, a policy valuing soil carbon in agricultural systems specifically indicates strong adoption of no-till and cover cropping for key crops. Conclusions We conclude that under targeted terrestrial carbon incentives, adoption of no-till and cover cropping practices in the US could increase the terrestrial carbon sink with limited effects on crop availability for food and fodder markets. Future work should consider integrated assessment modeling of non-CO 2 greenhouse gas impacts, above ground carbon storage changes, and capital and operating cost considerations.

54 ENVIRONMENTAL SCIENCES↗

Chapter 9: Human Behavior Dynamics in Sustainability

Human behavior dynamics and actions play a direct and significant role in shaping pathways toward sustainability, resulting in many sustainability challenges. A social dilemma arose when a hypothetical Colorado rural town closed down most of its medicine take-back stations as a result of reduced tax revenue. The current discourse discusses a scenario in which an individual "plays" against everyone else concerning whether to drive to the take-back station to dispose of unused medication (i.e., cooperating) or to flush it or throw it in the landfill (i.e., defecting). Using the structure of the pay-off matrix, this study analyzed unwanted medication disposal from a social dilemma perspective to provide insight into an individual's motivations to cooperate or defect and techniques for encouraging cooperation. The pay-off matrix encompasses four scenarios, namely, win-win when everyone cooperates, you're the sucker when only the individual cooperates, free rider when only the individual defects, and the tragedy of the commons when everyone defects. Reasons for an individual to cooperate include sharing the high moral value with everyone else, valuing social conformity, and taking great pride in doing the right thing, even when cooperating is costly. On the other hand, the individual who defects believes that cooperating will likely make little difference. The individual is selfish or insufficiently motivated by altruism and feels that the bad action will not get caught. When everyone defects, it likely results from participants not wanting to be a "sucker" and a lack of accountability (e.g., no punishment) associated with bad behavior. One solution to the free-rider problem is to appeal to the free rider's altruism. It is important to convince the individual that doing things for the benefit of others can also benefit themselves. Furthermore, a way to fix the social dilemma is to make the defectors pay for their actions that cause the negative externality (i.e., town water contaminated with pharmaceutical chemicals from unwanted medications). The higher the financial incentive for cooperative behavior, the lower the defecting propensity. By including punishment (e.g., discipline and penalty), people tend to defect less often, and highly cooperative outcomes emerge.

ENERGY PLANNING, POLICY, AND ECONOMY↗

A stochastic electricity market clearing formulation with consistent pricing properties

We argue that deterministic market clearing formulations introduce arbitrary distortions between day-ahead and expected real-time prices that bias economic incentives. We extend and analyze a previously proposed stochastic clearing formulation in which the social surplus function induces penalties between day-ahead and real-time quantities. We prove that the formulation yields price bounded price distortions, and we show that adding a similar penalty term to transmission flows and phase angles ensures boundedness throughout the network. We prove that when the price distortions are zero, day-ahead quantities equal a quantile of their real-time counterparts. The undesired effects of price distortions suggest that stochastic settings provide significant benefits over deterministic ones that go beyond social surplus improvements. Finally, we propose additional metrics to evaluate these benefits.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Data from Adopting Bioenergy Crops: Does Farmers’ Attitude Toward Loss Matter?

We apply prospect theory to examining farmers’ economic incentives to divert a share of their land to bioenergy crops (miscanthus and switchgrass in this study). Numerical simulation is conducted for 1,919 rain‐fed U.S. counties to identify the impact of loss aversion on bioenergy crop adoption, and how this impact is influenced by biomass price, discount rate, credit constraint status, and policy instruments. Results show that ignoring farmer’s loss aversion causes overestimation of miscanthus production but underestimation of switchgrass production, particularly when farmers are credit constrained and have a high discount rate. We find that establishment cost subsidy induces more miscanthus production whereas subsidized energy crop insurance induces more switchgrass production. The efficacy of these two policy instruments, measured by biomass production increased by per dollar of government outlay, depends on the magnitude of farmers’ loss aversion and discount rate.

Economics↗

Data for Spatially Varying Costs of GHG Abatement with Alternative Cellulosic Feedstocks for Sustainable Aviation Fuels

Cellulosic biomass-based sustainable aviation fuels (SAFs) can be produced from various feedstocks. The breakeven price and carbon intensity of these feedstock-to-SAF pathways are likely to differ across feedstocks and across spatial locations due to differences in feedstock attributes, productivity, opportunity costs of land for feedstock production, soil carbon effects, and feedstock composition. We integrate feedstock to fuel supply chain economics and life-cycle carbon accounting using the same system boundary to quantify and compare the spatially varying greenhouse gas (GHG) intensities and costs of GHG abatement with SAFs derived from four feedstocks (switchgrass, miscanthus, energy sorghum, and corn stover) at 4 km resolution across the U.S. rainfed region. We show that the optimal feedstock for each location differs depending on whether the incentive is to lower breakeven price, carbon intensity, or cost of carbon abatement with biomass or to have high biomass production per unit land. The cost of abating GHG emissions with SAF ranges from $181 Mg−1 CO2e to more than $444 Mg−1 CO2e and is lowest with miscanthus in the Midwest, switchgrass in the south, and energy sorghum in a relatively small region in the Great Plains. While corn stover-based SAF has the lowest breakeven price per gallon, it has the highest cost of abatement due to its relatively high GHG intensity. Our findings imply that different types of policies, such as volumetric targets, tax credits, and low carbon fuel standards, will differ in the mix of feedstocks they incentivize and locations where they are produced in the U.S. rainfed region. Note: Column V in TableS7_DayCentSimulatedYield.csv should be labelled Corn Stover CoSo-NT-50% Max.

Geospatial↗

Early prediction of antigenic transitions for influenza A/H3N2

Influenza A/H3N2 is a rapidly evolving virus which experiences major antigenic transitions every two to eight years. Anticipating the timing and outcome of transitions is critical to developing effective seasonal influenza vaccines. Using a published phylodynamic model of influenza transmission, we identified indicators of future evolutionary success for an emerging antigenic cluster and quantified fundamental trade-offs in our ability to make such predictions. The eventual fate of a new cluster depends on its initial epidemiological growth rate––which is a function of mutational load and population susceptibility to the cluster––along with the variance in growth rate across co-circulating viruses. Logistic regression can predict whether a cluster at 5% relative frequency will eventually succeed with ~80% sensitivity, providing up to eight months advance warning. As a cluster expands, the predictions improve while the lead-time for vaccine development and other interventions decreases. However, attempts to make comparable predictions from 12 years of empirical influenza surveillance data, which are far sparser and more coarse-grained, achieve only 56% sensitivity. By expanding influenza surveillance to obtain more granular estimates of the frequencies of and population-wide susceptibility to emerging viruses, we can better anticipate major antigenic transitions. This provides added incentives for accelerating the vaccine production cycle to reduce the lead time required for strain selection.

59 BASIC BIOLOGICAL SCIENCES↗

Trust based attachment

In social systems subject to indirect reciprocity, a positive reputation is key for increasing one’s likelihood of future positive interactions. The flow of gossip can amplify the impact of a person’s actions on their reputation depending on how widely it spreads across the social network, which leads to a percolation problem. To quantify this notion, we calculate the expected number of individuals, the “audience”, who find out about a particular interaction. For a potential donor, a larger audience constitutes higher reputational stakes, and thus a higher incentive, to perform “good” actions in line with current social norms. For a receiver, a larger audience therefore increases the trust that the partner will be cooperative. This idea can be used for an algorithm that generates social networks, which we call trust based attachment (TBA). TBA produces graphs that share crucial quantitative properties with real-world networks, such as high clustering, small-world behavior, and powerlaw degree distributions. We also show that TBA can be approximated by simple friend-of-friend routines based on triadic closure, which are known to be highly effective at generating realistic social network structures. Therefore, our work provides a new justification for triadic closure in social contexts based on notions of trust, gossip, and social information spread. These factors are thus identified as potential significant influences on how humans form social ties.

59 BASIC BIOLOGICAL SCIENCES↗

Recent advances in metal hydrides for clean energy applications

Metal hydrides are a fascinating class of materials that can be utilized for a surprising variety of clean energy applications, including smart solar collectors, smart windows, sensors, thermal energy storage, and batteries, in addition to their traditional application for hydrogen storage. Over the past decade, research on metal hydrides for hydrogen storage increased due to global governmental incentives and an increased focus on hydrogen storage research for polymer electrolyte membrane fuel cell operation. Tremendous progress has been made in so-called complex metal hydrides for hydrogen storage applications with the discovery of many new hydrides containing covalently bound complex anions. Many of these materials have applications beyond hydrogen storage and are being investigated for lithium-ion battery separator and anode materials. In this issue of MRS Bulletin , we present the state of the art of key evolving metal-hydride-based clean energy technologies with an outlook toward future needs.

batteries↗

Energy Communities IWG Site Review Tool

The Energy Communities IWG's new Site Review Tool is a resource for manufacturers and investors interested in developing or expanding clean energy supply chain projects in energy communities and nationwide. The interactive map provides access to publicly available information on brownfields, facilities, nearby infrastructure, and community attributes, including federal incentives. The site review tool empowers community leaders and developers to promote investment into communities and encourages users to learn and explore the diverse range of investment options. This tool can be useful for applicants to identify relevant information about their project that is requested in DOE grant and tax credit submissions, including 48C energy community status and whether a project is located in a disadvantaged community. More information on this tool can be found at: https://energycommunities.gov/iwg-site-review-tool/ Disclaimer: This mapping tool may not be relied upon by taxpayers to substantiate a tax return position or for determining whether certain penalties apply and will not be used by the IRS for examination purposes. The mapping tool does not reflect the application of the law to a specific taxpayer's situation, and the applicable Internal Revenue Code provisions ultimately control.

48C↗

Closing the data life cycle: using information management in macrosystems ecology research

An important goal of macrosystems ecology research is to advance understanding of ecological systems at both fine and broad temporal and spatial scales. Our premise in this paper is that such projects require information management that is integrated into projects from their inception. Such efforts will lead to improved communication and sharing of knowledge among diverse project participants, better science outcomes, and more open science. We promote "closing the data life cycle" by publishing well-documented data sets, which allows for re-use of data to answer new and different questions from the ones conceived by the original projects. The practice of documenting and submitting data sets to publicly accessible data repositories ensures that research results and data are accessible to and useable by other researchers, thus fostering open science. Ecologists are often not familiar with the information management tools and requirements to effectively preserve data, however, and receive little institutional or professional incentive to do so. This paper describes recommended steps to these ends, and gives examples from current macrosystem ecology projects of why information management is so critical to ensuring that scientific results can be both reproduced and data shared for future use.

Ruegg, Janine↗

Modeling City Building Stock for Large-Scale Energy Efficiency Improvements using CityBES

Buildings in San Francisco consumed 52% of total primary energy. Improving building energy efficiency is one of the key strategies cities are adopting towards their energy and climate goals. Urban building energy models (UBEM) can support city managers to evaluate and prioritize energy conservation measures for investment and to design effective incentive and rebate programs. This paper introduces methods to develop a standardized dataset of city building stock, and it demonstrates the use of a UBEM tool, City Building Energy Saver (CityBES), for an urban-scale energy retrofit analysis of building stock in the city of San Francisco. CityBES is an open web-based data and computing platform providing city-scale building energy modeling and performance visualization and benchmarking. CityBES utilizes an international standard CityGML to represent the three-dimensional building stock in cities. As an application example, 940 office and retail buildings in six districts of northeast San Francisco were modeled and analyzed with CityBES to evaluate energy savings for five selected measures. The analysis found that replacing existing lighting with LED and adding an air economizer to HVAC systems are cost-effective measures with combined savings per building between 17% to 31%. The CityBES retrofit analysis feature does not require users to have deep knowledge of building systems or building energy models, which helps overcome barriers for city managers and their consultants to adopt UBEM.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Mobilizing the anti-duck brigade: technology and market pathways for load-shifting demand response in California

With rapidly increasing renewable power generation, the California electricity system is experiencing the impacts of the so-called “duck curve,” with occasional over-generation in the middle of the day, followed by rapid ramping of net demand producing a sharp evening peak. Mitigating this pattern will require novel demand-side management approaches to shifting demand away from high net demand periods and toward high renewables generation periods. In this paper, drawing from more than 200,000 individual residential, commercial, and industrial customers’ hourly smart meter data, we disaggregate load shapes for certain key end-uses and then average the results across a highly granular set of customer segments by sector, building type, demand profile and geographic region, to yield a library of characteristic daily load profiles (“clusters”) for different end-uses and seasons. By categorizing the library into particularly desirable or undesirable load shapes in the context of mitigating the duck curve, we can gain insight into specific technologies, seasonal effects, or site-level attributes that may serve as helpful levers to use in developing future load-shifting programs. Based on these insights, we develop recommendations on technologies and new market structures and incentives that can create a future demand curve that more closely matches renewable generation patterns.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The BayREN Integrated Commercial Retrofits (BRICR) Project: An Introduction and Preliminary Results

BayREN Integrated Commercial Retrofits (BRICR) is a DOE-funded project which aims to enhance the capacity of energy efficiency programs to recruit participants, develop retrofits, and measure outcomes in small and medium-sized commercial buildings, a sector notoriously hard to reach and expensive to serve, that accounts for 2/3 of US commercial floor space. To address these barriers, BRICR leverages existing incentives, financing, data, and open source software to facilitate two paths for comprehensive improvements: a deep energy retrofit, or serial upgrades integrated into capital improvement and maintenance cycles. BRICR is developing an integrated workflow for iterative energy modeling of commercial buildings for city energy program managers and auditors - starting with mass building-scale simulation based on public records and proceeding through audit, retrofit, and measurement and verification stages. BRICR builds on existing tools including LBNL’s CBES, NREL’s OpenStudio, PNNL’s Audit Template, and DOE’s BuildingSync and SEED PlatformTM. At each stage, BRICR uses available information to inform simulations (starting with public records but iteratively augmented with observations from energy program staff) to improve the quality of the models that inform decision making. This paper presents initial results from energy models of 1699 office and retail buildings in San Francisco. Building stock data from public records were translated to create a BuildingSync file for each building which was stored in SEED. Each BuildingSync file was then translated to multiple OpenStudio Workflow files for EnergyPlus simulation to estimate energy savings of energy conservation measures (ECM). Energy savings predictions for each ECM were written back to an updated BuildingSync file for each building and re-uploaded to SEED. The distribution of baseline energy simulations was calibrated against the publicly disclosed distribution of energy benchmarking data to increase confidence in results.

Piette, M↗